Electroencephalograms (EEGs), magnetic electroencephalograms (MEGs) and the like are often used to detect, receive, process, convert, and record brain waves. The brain waves detected, received, processed, converted and recorded by these devices are often converted into signals that may be utilized to control other objects/devices, communicate with other objects/devices and/or other humans and the like.
U.S. Pat. No. 9,405,366, which is hereby incorporated by reference in its entirety to the extent not inconsistent with the present application, describes a device configured to detect, receive, process convert and record brain waves into signals that may be used to control other objects/devices and communicate with other objects/devices and/or other humans and the like.
Conventional devices that detect, receive process, convert and record brain waves into signals that may be utilized to control other objects/devices and communicate with other objects/devices, and/or other humans are presently often inaccurate and slow. For example, non-invasive devices that detect, receive, process, convert and record brain waves are often unable to accurately detect, receive, process, and record such brain waves due to shielding from the skull, the presence of other electrical signals around the patient (such as, for example as, cell phones and other electronic devices), noisy signal acquisition, low signal resolution, and the like. Furthermore, the ability to accurately detect, receive, process, convert and record brain waves may be impacted by the devices user's emotions, levels of concentration and the device's sensitivity. It is also difficult to identify the specific brain-signal of interest amongst all the different brain waves simultaneously detected by the device at any one time.
Additionally, the brain waves acquired by EEG and MEG-like devices may be difficult to detect, receive, process, record, and convert into signals used to control other objects/devices and communicate with other objects/devices and/or other humans. Often times, it is difficult to identify patterns within the brain waves that may be used to convert the brain waves (i.e., EEG data) into other signals used to control other objects and devices and/or communicate with other objects/devices and/or other humans due to the dynamic nature and high variability of detectable brain waves. To address this issue, many current devices require a training period (also referred to as “bio training”). During the training period, device users may train the device to identify brain wave patterns and associate them to specific executions or functions. However, the training period may require a user to undergo multiple training sessions and utilize specialized personnel to effectively and accurately train the device to detect the user's brain waves. Moreover, a user may be able to imagine certain thoughts more easily than other thoughts. For example, a user may have a preferred imagined direction that is easier to think about than others are. For this reason, it may be easier to train the device to detect the user's brain waves for some directions more easily than for others. These issues may prevent a device from being universally usable.
Additionally, because a large amount of individual EEG data must be processed in order to effectively and accurately isolate a specific pattern or signal of interest, currently there can be a long latency between when the user acquires the EEG data and when the brain wave signal is transmitted to control other devices. In other words, there is a long delay between when the user acquires the EEG data and when the signal is transmitted to control other objects/devices and or with other objects/devices and/or other humans that receive the transmitted signal is produced and/or implemented. For example, a state-of-the art brain wave to communication device in September 2016 allowed a monkey to type 12 words per minute (http://spectrum.ieee.org/the-human-os/biomedical/bionics/monkeys-type-12-words-per-minute-with-braintokeyboard-communication).
To obtain a higher signal resolution many devices that acquire brain waves include components that are implanted within the user's skull. Such devices are extremely invasive and required skilled personnel to implant, monitor, and use the device.
In an effort to address some of the issues discussed above, some current devices aim to link brain waves acquired by the device with easily identifiable behaviors such as eye-blinks, smiles, jaw clenches, and brow raises. These easily identifiable behaviors are often used to indicate the onset of a pattern or brain-signal of interest that should be converted into a signal to control other objects/devices, communicate with other objects/devices and/or other humans and the like. However, there remains a limited group of easily identifiable behaviors that may be linked to brain waves. Furthermore, many of the easily identifiable behaviors are overt and easily visible.